Decentralized Control Framework for Optimal Platoon Spacing and Energy Efficiency

This study introduces a decentralized control framework designed to improve energy efficiency in vehicle platooning by optimizing inter-vehicle gaps to minimize aerodynamic drag, a significant factor in energy consumption. The proposed framework integrates extremum seeking control (ESC), a proportional integral derivative controller with feedforward compensation (PIDFC), and an extended state observer for estimating aerodynamic drag coefficients. Through this integration, the ESC dynamically adjusts inter-vehicle gaps to minimize the drag force based on the estimated aerodynamic drag coefficients, while the PIDFC ensures precise tracking of the optimized gaps and effectively addresses disturbances arising from aerodynamic variations. The results show that the proposed ESC with PIDFC converged to the optimal distance gaps 37.14% faster than the ESC with PPC, within a steady-state error of ±1%. Additionally, it improved the computational efficiency by 70.6%, compared to the ESC with PPC. Furthermore, it reduced the energy consumption by 15.3%, compared to the fixed-gap approach. These findings demonstrate the framework’s potential to enhance the energy efficiency, scalability, and practicality, advancing sustainable and autonomous transportation systems.